1 Introduction
The topics of macroeconomics
At each point in time, individuals in an economy are making choices with respect to the acquisition, sale, and/or use of a variety of different goods. Such activity can be summarized by aggregate variables such as an economy's total production of various goods and services, the aggregate level of employment and unemployment, the general level of interest rates, and the overall level of prices.1 Macroeconomics is the study of movements in such economy-wide variables as output, employment, and prices.
The focus of this book will be on developing simple theoretical models that provide insight into the reasons for fluctuations in such aggregate variables. These models explore how shocks or âimpulsesâ to the economy (e.g., changes to technology, the money supply, or government policy) impact individualsâ behavior in specific markets and the resulting implications in terms of changes in aggregate variables.
An overview of some facets of theoretical macroeconomic analysis
Given the breadth of economic activity in an economy, the study of macroeconomics must involve an examination of a variety of different markets. For instance, it is common for macroeconomic analysis to consider exchanges of labor services in the labor markets, of consumption and capital goods in the output markets, and of financial assets in the financial markets. The fact that macroeconomics simultaneously analyses exchanges of different goods in different markets means that macroeconomic theory is a general equilibrium theory. That is, macroeconomic theory must by necessity incorporate the links across markets that are fundamental to general equilibrium analysis. As we will see throughout this book, a key reflection of the links across markets is Walrasâ law, named in honor of the nineteenth-century French economist, Leon Walras.2 Simply put, Walrasâ law notes that the budget constraints faced by individual agents in the economy suggest that if n â 1 of the n markets in the economy are in equilibrium, then the nth market must be in equilibrium. We will repeatedly rely on Walrasâ law or variants of it to simplify macroeconomic analysis.
While macroeconomic theories have in common (a) an attempt to explain fluctuations in aggregate variables and (b) a general equilibrium character, there remain wide differences among macroeconomic models. Below we break down these differences across macroeconomic models in several ways in order to make some sense of what passes for simple theoretical macroeconomic analysis.
Static, dynamic, and stationary analysis
One way of breaking down macroeconomic analyses is into static models, dynamic models, and stationary analysis of dynamic models. Static macroeconomic models analyze the economy at a point in time. They consider the determination of production, exchange, and prices of various goods only for the markets that currently exist. John Hicks (1939) sketched out an analysis of âspotâ or âtemporaryâ equilibrium. The advantage to such an approach is that it provides for rather simple âcomparative staticâ analysis of the effects of changes in a variety of exogenous variables on the endogenous variables.3 Such static analysis is useful in providing insight into a variety of questions of interest.
Static macroeconomic analysis can be viewed as a modification of a Walrasian general equilibrium analysis, or what is commonly referred to as âArrowâDebreu theoryâ (Arrow and Hahn 1971; Debreu 1959). In ArrowâDebreu theory, each commodity is described by its physical characteristics, its location, and its date of availability. It is assumed there are a complete set of spot and forward markets. Prices adjust to clear all markets. However, if one restricts attention to just spot markets, then one moves from traditional Walrasian general equilibrium to an analysis of âtemporary equilibrium,â a phrase coined by Hicks (1939). This restriction to spot markets is one element of static macroeconomic analysis.4
A second element of static models is that if there is a future, then static macroeconomic analysis simply assumes given expectations of future prices and environment. How expectations of future events are formed is left unspecified, so that expectations of future prices become simply an element in the set of exogenous variables.5
While static analysis provides insights, there are several disadvantages of static analysis severe enough that it alone does not provide an adequate grounding in macroeconomic analysis. The key disadvantage of static analysis is that it breaks ties between current events and future events. To show the limitations of static analysis, let us suppose that underlying a simple static macroeconomic analysis of current markets is a microeconomic analysis of individualsâ decisions that identifies the anticipated future level of prices as one of the exogenous variables affecting current behavior. As we have seen, static analysis takes expectations of such variables as future prices as exogenous variables. Doing so, however, results in (a) an incomplete enumeration of exogenous variables that can impact current economic activity and (b) a potentially incomplete accounting of the effects of the impact on current economic activity of a change in those exogenous variables that are identified by the analysis.
To illustrate the first point of an incomplete listing of exogenous variables, let us suppose that the static model identifies changes in the current money supply as one factor that influences current prices. This suggests that if we replicate the static analysis in future periods, changes in the money supply in the future would be shown to affect prices at that time. It seems natural to then presume that individualsâ anticipation of future prices would incorporate this link between changes in the future money supply and future prices in forming their expectations of future price levels, so that the anticipated future money supply becomes a determinant of current activity.6 Yet static analysis, since it does not analyze markets beyond the current period, will not identify the potential impact of future changes in the money supply on current activity.7
To illustrate the second point of an incomplete accounting of the effects of a change in an exogenous variable, let us suppose that underlying the static macroeconomic analysis of current markets is a microeconomic analysis of firmsâ current investment behavior that identifies the anticipated future tax levels as well as future prices as two exogenous variables affecting investment decisions. Thus, static analysis would suggest that a change in future tax levels will impact current activity through the direct effect on current investment. It is not hard to see, however, that (a) the current change in investment means a different future capital stock and (b) the change in future tax levels could affect future as well as current investment. Either or both of these changes would likely impact future prices and, if such an impact were anticipated, be a second way that future tax changes impact current activity.8
An obvious way to avoid the above problems is to introduce forward markets, so that the macroeconomic analysis determines the prices of goods to be traded in the future along with the prices of goods traded at the current time.9 In doing so, we have moved from static to dynamic analysis. That is, the macroeconomic models now determine the paths of variables (such as prices) over time rather than prices (and other variables) at only one point in time.
In a deterministic setting, this expansion of dynamic analysis incorporates the notion of âperfect foresight,â in which individuals correctly anticipate all future prices. If there were uncertainty, the analysis indexes goods by both the date of trade and the âstate of nature,â with trades contingent on the realized state of nature.10 The result is that at each date there is a distribution of potential prices at which trade for a good could occur and, given common knowledge of likelihood of the states of nature, expectations of future prices would be defined by the analysis (ârational expectationsâ).
Once dynamic analysis is introduced, we can consider a special limiting form of dynamic analysis, termed stationary analysis. The aim of stationary analysis is to identify in the context of a dynamic model the limiting tendencies of endogenous variables such as the capital stock or the rate of growth in prices given that the exogenous variables remain constant or stationary over time.11
While stationary analysis is distinct from static analysis, in some cases one can think of static analysis as a form of stationary analysis. That is, static analysis in some cases can be viewed as the outcome that would emerge each period given that the exogenous variables remain constant (or in some cases grow at a steady rate over time) and given that one picks the correct fixed level of certain key exogenous variables (e.g., the capital stock and the rate of change in the money supply). Note, however, that this implies that for static analysis to perfectly mimic stationary analysis, one must to all intents and purposes have first executed the underlying dynamic analysis.
Period (discrete) versus continuous-time analysis
Macroeconomic analysis can be broken down into period or discrete-time macroeconomic models and continuous-time macroeconomic models. Substantive differences in terms of theoretical predictions do not exist between these two types of analyses if one is careful to assure identical underlying assumptions. Yet the two analyses do differ in the analytical techniques used. For instance, while discrete macroeconomics relies on the techniques of dynamic programming and difference equations to characterize elements of the model, in similar circumstances continuous macroeconomic analysis turns to the techniques of optimal control and differential equations.
Although substantive issues are not raised by the discrete- versus continuous-time dichotomy, it is sometimes argued that one is preferred to the other. For instance, an attractive feature of the continuous-time analysis is that it highlights quite clearly the distinctions between stocks and flows, something that is not so clearly discernable in discrete analysis. On the other hand, an attractive feature of discrete analysis is that it makes more transparent the link between the theoretical analysis and empirical testing, since such analysis coincides with the obvious fact that empirical data on macroeconomic variables is discrete.
New classical economics versus non-market-clearing
Classical analysis refers to the widely adopted view of how the macroeconomy should be modeled that existed prior to the experience of the Great Depression and John Maynard Keynesâ General Theory of Employment, Interest, and Money (1936). In classical theory, the real side of the economy was separate from the money side. Classical analysis of the ârealâ side of the economy is aimed at determining such variables as total production, relative prices, the real rate of interest, and the distribution of output. Classical analysis of the money side of the economy meant analysis is aimed at determining money prices and nominal interest rates.
The separation of the monetary side from the real side in classical or neoclassical analysis led to the prediction that monetary changes do not have any effect on real variables such as total output.12 A similar prediction is often obtained by more recent macroeconomic analysis, and this is one reason why this more recent analysis is referred to as the new classical economics.13 Alternative labels of these new classical models include: rational expectations models with market clearing, neoclassical models of business fluctuations, and equilibrium business cycle models.
A common feature of the analyses of new classical economics, besides the fact that it suggests a divorcement of monetary changes from the real side of the economy, is that prices are determined in the analysis so as to clear markets. This view that prices serve to equate demands and supplies, a view common to microeconomics, is taken as an important strength of the analysis for it means that the models have consistent âmicroeconomic foundations.â One implication of the market-clearing assumption is the same as in microeconomics â the analysis suggests that all gains to exchange have been extracted.
Contrasting the new classical economics with what preceded it helps one put this rebirth of classical analysis into perspective. Following the Great Depression, macroeconomic analysis took as its main premise the idea that markets did not clear â in particular, that prices did not adjust. In this context, the business cycle was defined by âmarket failure,â and the role of government to stabilize the economy was clear. There are a number of different types of non-market-clearing, or Keynesian, models. One version of such Keynesian models, that popularized by Patinkin (1965, chapters 13â14), Clower (1965), and Barro and Grossman (1971), takes as given output prices, such that the output market fails to clear. A second model, popularized by Fischer (1977), Phelps and Taylor (1977), and Sargent (1987a) as an alternative formalization of the Keynesian model, takes as given the price of labor, such that the labor market fails to clear.
The common theme of these non-market-clearing analyses is that for various reasons prices do not clear markets and concepts such as excess demand and supply play a role in the analysis. Yet no concise reason is given as to why there is market failure other than suggesting such items as âcoordination problemsâ and âtransaction costs.â14 The result is that such analysis is challenged by the new classical economics as lacking the microeconomic foundations for price determination. As Howitt (1986: 108) suggests, such a view âforces the proponent of active stabilization policy to explain the precise nature of the impediments of transacting and communicating that prevent private arrangements from exhausting all gains from trade.â15 This is not an easy task according to Howitt, since âimpediments to communication in a model simple enough for an economist to understand will typically also be simple enough that the economist can think of institutional changes that would overcome themâ (1989: 108).
Microeconomic foundations and aggregation issues
An important feature of macroeconomic analysis is that it reflects the aggregation of individual decisions. A common approach to such aggregation is to assume ârepresentativeâ agents, characterize their optimal behavior, then use such behavioral specifications in building the macroeconomic model. Thus, much of macroeconomic analysis entails looking at individualsâ decisions, such as householdsâ decisions to work, consume, and save or firmsâ decisions to produce, borrow, and invest in capital.
These characterizations of optimizing individual behavior make up part of the building blocks, or âmicroeconomic foundations,â of macroeconomic analysis. Yet microeconomic foundations of macroeconomics are not restricted to such analysis. For instance, such foundations also include a characterization of how prices in individual markets are determined, as we saw in our discussion of new classical economics.
In developing the microeconomic foundations of macroeconomic models, we will often be struck by the extent to which the analysis restricts any role for heterogeneity or diversity among the individual agents in the economy. Yet such diversity can in certain instances be critical to the analysis. One attempt to introduce diverse or heterogeneous agents into macroeconomic analysis is represented by the overlapping generations models. These models also have the advantage of being genuinely dynamic in nature, and as such represent one area of macroeconomics that has recently received significant attention.
Deterministic versus stochastic
In recent years, an important element to macroeconomic models has been to introduce stochastic elements. The rationale is clear: the presence of uncertainty as to future events is real. As noted by Lucas (1981: 286),
the idea that speculative elements play a key role in business cycles, that these events seem to involve agents reacting to imperfect signals in a way which, after the fact, appears inappropriate, has been commonplace in the verbal tradition of business cycle theory at least since Mitchell ⌠It is now entirely practical to view price and quantity paths that follow complicated stochastic processes as equilibrium âpointsâ in an appropriately specified space.
As the quote suggests, in dynamic models, especially for new classical economics where market clearing is presumed, stochastic elements are incorporated into the analysis, so that the role played by shocks to an economy in a dynamic setting can be well d...